基于MODIS数据的松嫩草原产草量遥感估算模型与空间反演

    Models for estimation of grassland production and spatial inversion based on MODIS data in Songnen Plain

    • 摘要: 根据NASA/MODIS遥感数据获得NDVI、RVI、MSAVI和EVI 4种植被指数,结合草原产草量地面实测数据,利用统计分析方法建立松嫩草原产草量遥感估算模型,并进行产草量空间反演和验证,为该区草原产草量合理估算和草原资源管理提供科学依据。相关分析结果表明,前期和同期的4种植被指数均与草原产草量显著相关,其中NDVI相关性最高,EVI相关性最低;松嫩草原产草量最优模拟模型为基于NDVI的S曲线模型,模拟精度达78%。利用该模型反演得到2009年松嫩草原平均鲜草单产为5 717 kg/hm2,折合干草单产1 687 kg/hm2,鲜草总产量为1 885万t,干草总产量为589万t。其中,黑龙江省部分的鲜草总产量为1 356万t,折合干草424万t;吉林省部分的鲜草和干草总产量分别为531万t和166万t。利用植被指数预报未来16 d草原产草量效果较好,其中基于NDVI的幂指数模型预报精度为74%。研究表明,基于植被指数进行松嫩草原产草量研究是可行的。

       

      Abstract: Using NASA/MODIS data to calculate NDVI, RVI, MSAVI and EVI four vegetation indexes, combining grass production(green weight)data, by means of statistical methods, estimation models of grass production in Songnen Plain were established, for the sake of estimating yield of grass reasonably and regulating grassland resources. With the correlation analysis, it was found that all of the four prophase and synchronous vegetation indexes were correlated with grass production(green weight)significantly, among them NDVI had the highest correlation coefficient and EVI the lowest. The best estimation model of grass production in Songnen Plain was S curve model based on NDVI, with estimation accuracy 78%. Calculating yield of grass in Songnen Plain through the best estimation model, total fresh yield was 18 850 thousand tons, equivalent to 5 890 thousand tons of hay, and fresh weight per unit area was 5 717 kg/hm2, equaling to 1 687 kg/hm2 of dry weight. Total fresh yield belong to Heilongjiang Province was 13 560 thousand tons, equivalent to 4 240 thousand tons of hay, and yield of fresh grass and hay belong to Jilin Province was 5 310 and 1 660 thousand tons separately. Using vegetation indexes to predicting future sixteen days’ grass yield was proved nice, and the prediction accuracy of exponential model based on NDVI was 74%. The research shows that it is feasible to study grass production of Songnen Plain with vegetation indexes.

       

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